diff --git a/docs/my-website/docs/completion/batching.md b/docs/my-website/docs/completion/batching.md
index af30f5678..5c278aebe 100644
--- a/docs/my-website/docs/completion/batching.md
+++ b/docs/my-website/docs/completion/batching.md
@@ -1,4 +1,9 @@
 # Batching Completion() Calls 
+LiteLLM allows you to:
+* Send multiple completion calls to 1 model
+* Send 1 completion call to N models
+
+## Send multiple completion calls to 1 model
 
 In the batch_completion method, you provide a list of `messages` where each sub-list of messages is passed to `litellm.completion()`, allowing you to process multiple prompts efficiently in a single API call.
 
@@ -6,7 +11,7 @@ In the batch_completion method, you provide a list of `messages` where each sub-
   <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
 </a>
 
-## Example Code
+### Example Code
 ```python
 import litellm
 import os
@@ -32,4 +37,53 @@ responses = batch_completion(
         ]
     ]
 )
+```
+
+## Send 1 completion call to N models
+This makes parallel calls to the specified `models` and returns the first response 
+
+Use this to reduce latency
+
+### Example Code
+```python
+import litellm
+import os
+from litellm import batch_completion_models
+
+os.environ['ANTHROPIC_API_KEY'] = ""
+os.environ['OPENAI_API_KEY'] = ""
+os.environ['COHERE_API_KEY'] = ""
+
+response = batch_completion_models(
+    models=["gpt-3.5-turbo", "claude-instant-1.2", "command-nightly"], 
+    messages=[{"role": "user", "content": "Hey, how's it going"}]
+)
+print(result)
+```
+
+### Output
+Returns the first response
+```json
+{
+  "object": "chat.completion",
+  "choices": [
+    {
+      "finish_reason": "stop",
+      "index": 0,
+      "message": {
+        "content": " I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, harmless, and honest.",
+        "role": "assistant",
+        "logprobs": null
+      }
+    }
+  ],
+  "id": "chatcmpl-23273eed-e351-41be-a492-bafcf5cf3274",
+  "created": 1695154628.2076092,
+  "model": "command-nightly",
+  "usage": {
+    "prompt_tokens": 6,
+    "completion_tokens": 14,
+    "total_tokens": 20
+  }
+}
 ```
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